How Cashinvoice Is Making Credit Access Smarter for MSMEs

Arun Poojari, CEO & co-founder of Cashinvoice, explains how digital SCF, e-invoicing, and fintech-led inclusion are redefining MSME credit access beyond metros.

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Manisha Sharma
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Arun Poojari

As India’s MSME ecosystem evolves into the backbone of the country’s $5-trillion economy vision, access to timely and affordable credit remains its biggest challenge. Digital supply chain finance (SCF) platforms are emerging as powerful enablers, bridging liquidity gaps and bringing financial inclusion to Tier-II and Tier-III cities.

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In a conversation with CiOL, Arun Poojari, CEO and co-founder of Cashinvoice, shared how the company is leveraging invoice-backed financing, e-invoicing infrastructure, and data-driven credit assessment to redefine MSME lending and accelerate economic growth across Bharat.

Interview Excerpts:

What structural factors are driving faster credit adoption among MSMEs in Tier II and III cities compared to metro businesses?

Faster credit adoption among MSMEs in Tier II and III cities is driven by both policy and structural factors. Government initiatives like MUDRA and the Credit Guarantee Fund Trust (CGTMSE) provide lenders with guarantees, enabling MSMEs to access credit without collateral. 

Digital Public Infrastructure like Account Aggregator framework, GST and e-invoicing has also brought smaller businesses into the formal economy. These have improved transparency and allowed lenders to evaluate creditworthiness based on cash flows rather than collateral. At the same time, fintech lenders and NBFCs have expanded aggressively into these markets, further boosting formal credit access.

Structurally, anchor-based supply chain financing (SCF) is also supporting this adoption. Smaller suppliers and distributors plugged into large corporate ecosystems can now access formal credit at lower costs due to the anchor’s stronger credit profile. Platforms like TReDS (Trade Receivables Discounting System) have further accelerated adoption by allowing MSMEs to discount invoices digitally, ensuring quicker access to working capital.

Industry voices describe digital supply chain finance as India’s potential “UPI moment” for business lending — what would need to change in terms of infrastructure, adoption, or regulation for that to become reality?

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For Supply chain financing to realize its “UPI” vision, several structural shifts are needed. A significant aspect would be on the infrastructure front. The ecosystem needs interoperable digital platforms that can seamlessly connect buyers, suppliers, and financiers. Similar to how UPI created a common set of communication for payments, SCF will need a standardized data exchange for purchase orders, invoices, and expenses. Integration with GST, e-invoicing, and e-way bill is also crucial for building transparent transaction trails and minimizing risks such as double financing or fraudulent invoicing. 

Equally important is adoption. Many MSMEs, particularly in Tier II and III markets, are unfamiliar with SCF solutions. Simplified onboarding, vernacular interfaces, and trust-building through anchor businesses can accelerate usage. When large buyers participate in structured financing programs, smaller suppliers gain confidence and quicker access to liquidity.This is critical because limited access to affordable trade finance has long held back MSMEs.

The trade finance gap* in India, which, as per reports, ranges between 25-30 lakh crores results in stunting business growth and disproportionately affects women-led businesses.SCF can bridge this gap, making financing faster, more inclusive, and more efficient.

*(the difference between funds available and what businesses receive through letters of credit, trade loans, and other instruments)

What once took weeks or months in traditional lending cycles can now happen in minutes. For example, through our collaboration with the Bank of India, we launched a 30-minute MSME loan initiative that disburses working capital almost instantly, targeting ₹1,000 crore in credit for over two lakh MSMEs. If scaled nationally, such innovations could give SCF its true UPI-like breakthrough for Indian business lending.

For first-time borrowers and businesses new to formal credit, which underwriting signals and data sources are proving most reliable, and how do default patterns compare to traditional MSME lending?

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For first-time and new-to-credit businesses, the most reliable indicators of creditworthiness come from real-time financial and operational data, such as bank transactions, e-invoices, GST filings, tax records, and the Account Aggregator framework.

Anchor-backed SCF programmes enable first-time borrowers (often "thin-file" MSMEs without credit history) to access formal finance at affordable rates. Globally, through transactional isolation and buyer-backed security, default rates remain below 0.3%. This approach empowers lenders with more reliable credit decisions, yielding default rates far lower than traditional MSME lending (typically 4-6%).

Unlike traditional MSME lending, which depends heavily on historical credit scores and past financial statements, real-time insights provide a sharper view of a borrower’s current repayment capacity. Looking ahead, AI will amplify this by analysing patterns, spotting early warning signs, and predicting repayment or default likelihood from signals like repayment anomalies and industry macros.

Women-led MSMEs remain under-represented in invoice-backed financing — what barriers do they face, and what interventions have shown measurable success in bridging this gap?

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One of the primary barriers that women-owned businesses face is limited access to formal capital. Traditional lending models often rely on collateral, property ownership, or credit histories, areas in which women entrepreneurs have historically faced disproportionate disadvantages. Additionally, in many regions, women are unable to own property legally or have limited control over family assets, which restricts their ability to secure loans.

Lengthy documentation, manual approval processes, and rigid eligibility criteria also deter women entrepreneurs, particularly those managing micro or small enterprises while balancing family responsibilities. Furthermore, enforcement and awareness gaps in financial inclusion schemes often mean that women-led businesses are either unaware of opportunities or unable to effectively leverage them.

However, several interventions have shown measurable success in addressing these barriers. Collateral-free financing models specifically targeting women-led MSMEs have proven effective in multiple markets, allowing entrepreneurs to access working capital without needing property-backed guarantees. 

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Several initiatives support women-led MSMEs in building their credit histories, including  Self-Help Groups (SHG) and Joint Liability Groups (JLG). JLGs, a cornerstone of India’s microfinance sector, help women - particularly in rural areas - access credit collectively, with members jointly ensuring loan repayment, thereby reducing the need for traditional collateral.

Similarly, SHGs have enabled women to pool savings, establish credit histories, and access small loans together, addressing challenges related to limited collateral and property ownership. Banks and NBFCs often extend credit to SHGs or their members using group guarantees instead of individual collateral, providing a pathway to more structured financing such as invoice-backed loans.

How is invoice-backed financing contributing to India’s broader push for formalisation, and what risks — such as invoice duplication or misuse — should regulators and platforms guard against?

Invoice-backed financing is playing a key role in India’s broader push for formalisation by enabling businesses, particularly MSMEs, to access credit based on their receivables. Invoice based financing considerably reduces risk for financiers as the credit risk is limited to each transaction. The risk shifts to the borrower's customers (often larger, stable entities) whose payment history is assessed, lowering exposure to the borrower's potentially weak credit profile.

However, this comes with its risks, such as invoice duplication and invoice manipulation. These risks are especially pronounced in cash-heavy sectors or among enterprises with limited digital record-keeping. Regulators and platforms can address these challenges with centralised verification linked to e-invoicing, tamper-proof ledgers or blockchain solutions with mandatory buyer confirmation, and risk rule engines to flag anomalies.

Since August 1, 2023, the CBIC already requires businesses with annual turnover above ₹5 crore to generate e-invoices for all B2B, B2G, and export transactions under GST. This measure aims to enhance tax compliance, reduce fraud, and improve transparency. Combining such clear regulatory guidance with strong enforcement and regular audits can help strengthen the integrity of invoice-backed financing.

As digital SCF platforms scale, how are lenders and marketplaces addressing systemic risks like fraud, double-discounting, buyer concentration, and liquidity shocks?

As technology advances, lenders and marketplaces are implementing robust safeguards to mitigate systemic risks such as fraud, double discounting, buyer concentration, and liquidity shocks. Solutions like e-invoicing systems, real-time data integrations, and advanced fraud detection tools help ensure invoice authenticity and prevent duplicate financing. Complementing these technological measures, the RBI in 2016 introduced frameworks to disincentivise banks from lending excessively to very large corporate borrowers, thereby managing concentration risks. 

Blockchain technology is also emerging as a solution for these dynamic challenges. Through a blockchain-enabled SCF ecosystem, all transactions are recorded on a secure, immutable ledger that is visible to all participants. This increases transparency, prevents invoice duplication, and reduces the risk of fraud. Additionally, smart contracts can automate approval and payment processes, ensuring trust is built into the system rather than assumed.